Role overview
Hidonix is seeking an AI / Machine Learning Engineer to help design and implement intelligent systems that extract meaning and predictive value from computer vision and behavioral datasets. This is a junior-level, in-person role suited for candidates with 2–3 years of experience and a solid foundation in deep learning, embeddings, and modern neural architectures.
As a member of the AI team, the ideal candidate will work on projects that leverage CNNs, transformer models, and embedding architectures to encode and reason over pose, facial, and action-based visual data. These systems support downstream tasks such as future action prediction, semantic matching, and similarity-based inference.
Responsibilities
- Design and implement machine learning pipelines that encode visual input (pose, face, object/classification) into shared embedding spaces for similarity and predictive tasks
- Build and fine-tune convolutional and transformer-based neural architectures optimized for visual recognition and representation learning
- Develop encoding and embedding techniques that allow consistent comparison across multiple data types (e.g., pose vectors, facial landmarks, class labels)
- Apply techniques such as cosine similarity, distance metrics, and latent clustering to perform behavioral inference and action prediction
- Contribute to model training, evaluation, and deployment workflows including data preprocessing, augmentation, hyperparameter tuning, and performance profiling
- Collaborate closely with engineers in computer vision, embedded systems, software, and UI/UX to ensure seamless integration of AI pipelines into real-time systems
- Produce clean, well-documented code and maintain version-controlled model artifacts and experiment logs
- Write technical documentation for models, training procedures, evaluation criteria, and system integration
- Bachelor’s or Master’s degree in Artificial Intelligence, Data Science, Computer Science, Machine Learning, or a closely related discipline
- 2–3 years of experience in machine learning roles through internships, academic labs, or early career positions
- Strong understanding of:
- Convolutional Neural Networks (CNNs) for image and video-based tasks
- Transformer architectures and their applications in vision or multimodal learning
- Embedding systems and vector space modeling for semantic and similarity-based tasks
- Encoding mechanisms and dimensionality reduction techniques for latent representation
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Familiarity with pose estimation, facial recognition, or classification models (e.g., OpenPose, MediaPipe, FaceNet, ResNet variants)
- Experience training models with structured and unstructured visual datasets
- Exposure to techniques like cosine similarity, triplet loss, contrastive learning, or temporal prediction modeling
- Strong computer science fundamentals, including data structures, algorithms, and software design patterns
- Comfort working in Linux-based development environments and version control systems (Git)
- A collaborative mindset, with excellent communication skills and a willingness to learn across domains
- Experience integrating vision-based AI models into embedded or robotics systems
- Familiarity with ONNX or TensorRT for model optimization and deployment
- Background in sequence modeling, recurrent architectures, or video-based action recognition
- Exposure to multimodal AI systems that blend image, pose, and metadata representations
- Familiarity with techniques like CLIP, DINO, or self-supervised representation learning
- Experience with MLOps or training orchestration tools such as MLflow, Weights & Biases, or DVC
Benefits
- Full Health Coverage
- A collaborative and intellectually driven team environment
- Flexible PTO
- We are currently not accepting applications from third-party recruiting services
- We are not offering visa sponsorship for this role at this time. Applicants must be U.S. citizens or permanent residents (Green Card holders)
- Candidates must reside within a commutable distance of Santa Monica, California.
Tags & focus areas
Used for matching and alerts on DevFound Fulltime Ai Machine Learning Deep Learning Computer Vision